Adrian Bonilla-Petriciolet

Dynamic analysis of thermally coupled distillation sequences with undirectional flows for the separation of ternary mixtures

The Petlyuk distillation system has been considered with special interest because of the high energy savings it can provide with respect to the operation of sequences based on conventional columns. The original design of the Petlyuk structure, however, shows two interconnections that seem to affect its operational and controllability properties. To overcome this problem, two alternate structures have been suggested that use unidirectional flows of the vapor or liquid interconnecting streams. In this work, a comparative analysis of the control properties of the Petlyuk column and the alternate arrangements with unidirectional interconnecting flows is presented. Through a singular value decomposition analysis, it is shown that the alternate schemes provide better theoretical controllability properties than the Petlyuk system. Closed loop tests using proportional-integral controllers were also carried out, and the results showed that, in most of the cases considered, the alternate arrangements improved the dynamic responses of the Petlyuk column. Such arrangements, therefore, show promising perspectives for its practical consideration.

Adsorption Processes for Water Treatment and Purification

This chapter covers fundamental aspects of adsorption process engineering. In particular, the importance of adsorption processes for water treatment is discussed and analyzed. Environmental impact of some key aquatic pollutants is also reviewed. Opportunity areas for adsorption process intensification are also highlighted in this chapter including a brief overview of the content of this book.

Evaluation of Stochastic Global Optimization Methods in the Design of Complex Distillation Configurations

Distillation is a widely used separation process and is a very large consumer of energy. In process design, a significant amount of research work has been done to improve the energy efficiency of distillation systems in terms of either the design of optimal distillation schemes or for improving internal column efficiency. Still, the optimal design of multicomponent distillation systems remains one of the most challenging problems in process engineering (Kim & Wankat, 2004). The economic importance of distillation separations has been a driving force for the research in synthesis procedures for more than 30 years. For the separation of an N-component mixture into N pure products, as the number of components increases, the number of possible simple column configurations sharply increases. Therefore, the design and optimization of a distillation column involves the selection of the configuration and the operating conditions to minimize the total investment and operation cost (Yeomans & Grossmann, 2000). The global optimization of a complex distillation system is usually characterized as being of large problem size, since the significant number of strongly nonlinear equations results in serious difficulty in solving the model. Moreover, good initial values are needed for solving the NLP subproblems. Until now, several strategies have been proposed to address this optimization problem. For example, Andrecovich & Westerberg (1985) proposed a mixed-integer linear programming (MILP) model for synthesizing sharp separation sequences. Later, Paules & Floudas (1990) and Aggarwal & Floudas (1990) developed mixed-integer nonlinear programming (MINLP) models for heat-integrated and nonsharp distillation sequences using linear mass balances. In other study, Novak et al. (1996) proposed superstructure MINLP optimization approaches using short-cut models for heat-integrated distillation. Smith & Pantelides (1995) and Bauer & Stichlmair (1998) developed MINLP models using rigorous tray-by-tray models for zeotropic and azeotropic mixtures. Also, Dunnebier & Pantelides (1999) have used rigorous tray-by-tray MINLP models to solve complex column configuration

Applications of activated carbons obtained from lignocellulosic materials for the wastewater treatment

Activated carbons are used in a number of industrial applications including separation and purification technologies, catalytic processes, biomedical engineering, and energy storage, among others. The extensive application of activated carbon is mainly due to its relatively lowcost with respect to other adsorbents, wide availability, high performance in adsorption processes, surface reactivity and the versatility to modify its physical and chemical properties for synthesizing adsorbents with very specific characteristics (Haro et al., 2011). In particular, the adsorption on activated carbon is the most used method for wastewater treatment because it is considered a low-cost purification process where trace amounts of several pollutants can be effectively removed from aqueous solution. Recently, the demand of activated carbons has increased significantly as a water-purifying agent to reduce the environmental risks caused by the water pollution worldwide (Altenor et al., 2009; Bello-Huitle et al., 2010).

Process Intensification in Chemical Engineering – Design Optimization and Control

This chapter provides an overview of process intensification in chemical engineering and summarizes the content of this book. The chemical, pharmaceutical, and bio-based industries produce products that are essential for modern society. Nevertheless, these industries face considerable challenges because of the need to develop sustainable production methods for the future. Process intensification (PI) targets dramatic improvements in manufacturing and processing by rethinking existing operation schemes into ones that are both more precise and efficient than existing operations. PI frequently involves combining separate unit operations such as reaction and separation into a single piece of equipment resulting in a more efficient, cleaner, and economical manufacturing process. At the molecular level, PI technologies significantly enhance mixing, which improves mass and heat transfer, reaction kinetics, yields, and specificity. These improvements translate into reductions in equipment numbers, facility footprint, and process complexity, and, thereby, minimize cost and risk in chemical manufacturing facilities. In the frame of globalization and sustainability, the future of chemical engineering can be summarized in four main objectives: 1. Increase productivity and selectivity through intensification of intelligent operations and amultiscale approach to processes control (e.g., nanoor microtailoring of catalyst materials). 2. Design novel equipment based on scientific principles and new production methods: process intensification in using multifunctional reactors, microengineering, and microtechnology. J.G. Segovia-Hernández (*) Deptamento de Ingenieria Quimica, Universidad de Guanajuato, Noria Alta s/n, Guanajuato, Gto 36050, Mexico e-mail: gsegovia@ugto.mx A. Bonilla-Petriciolet Instituto Tecnol ogico de Aguascalientes, Av. L opez Mateos 1801, Aguascalientes 20256, Aguascalientes, Mexico e-mail: petriciolet@hotmail.com

Phase Equilibrium Modeling in Non-Reactive Systems Using Harmony Search

In recent years, a significant work has been performed in the area of software development for solving global optimization problems in science and engineering applications (Floudas et al., 1999). In particular, global optimization has and continues to play a major role in the design, operation, scheduling and managing of chemical industrial processes and, according to several authors; it will remain as a major challenge for future research efforts (Floudas et al., 1999; Biegler & Grossmann, 2004; Grossmann & Biegler, 2004; Rangaiah, 2010). In the context of chemical engineering, several algorithmic and computational contributions of global optimization have been used for process optimization. As expected, finding the global optimum is more challenging than finding a local optimum and, in some applications such as the phase equilibrium modeling, the location of this global optimum is crucial because it corresponds to the correct and desirable solution (Floudas et al., 1999; Teh & Rangaiah, 2002; Wakeham & Stateva, 2004; Rangaiah, 2010). Specifically, the modeling of phase equilibrium in multicomponent systems is essential in the design, operation, optimization and control of separation schemes. The phase behavior of multicomponent systems has a significant impact in several issues of process design including the determination of the equipment and energy costs of separation and purification strategies (Wakeham & Stateva, 2004). Note that phase equilibrium calculations (PEC) are usually executed thousands of times in process simulators and, as a consequence, these calculations must be performed, reliably and efficiently, to avoid design uncertainties and erroneous conclusions about process performance. However, literature indicates that the development of reliable methods for PEC has long been a challenge and is still a research topic of continual interest in the chemical engineering community (Teh & Rangaiah, 2002; Wakeham & Stateva, 2004). Basically, PEC involve two main problems: a) phase stability analysis is used to determine if a tested system under specified operating conditions is stable or not, and b) phase split calculations are performed to establish the number and identity (i.e., composition and type) of phases existing at the equilibrium (Wakeham & Stateva, 2004). These thermodynamic calculations can be formulated as global optimization problems where the tangent plane

Stochastic Optimization for Process Intensification

This chapter describes and discusses stochastic optimization methods for solving problems involved in process intensification, given an emphasis in multiobjective optimization due to its increasing importance in the chemical engineering community. A brief description of the multiobjective optimization strategies such as genetic algorithms, simulated annealing, tabu search, differential evolution, ant colony and particle swarm optimization is provided, including several applications of evolutionary optimization methods in the intensification of separation processes.

Surface structure changes in cement paste exposed to 10.6μm laser radiation

We report the changes occurring in cement pastes irradiated by 10.6μm CO2 laser at different stages of hydration. Raman spectroscopy, X-rays and Scanning Electronic Microscopy (SEM) techniques had been used to observe molecular structural changes. Intensity of cement paste Raman peaks after laser irradiation was monitored in samples irradiated 2, 3, 4, 5, 6, 7, 8, 9, 10 and 11 days after their preparation. Applied laser power changed Raman peaks intensity at 187.5cm-1, 563cm-1, 695cm-1, 750cm-1, 897cm-1, 1042cm-1 and 1159cm-1 that corresponds to compounds already presents in cement pastes. X ray diffraction and SEM images confirm the recrystalization of cement paste compounds into new phases (alite and belite) after irradiation. The produced changes show a clear dependence on the applied laser power density and age of samples.